• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.117-126
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• 2009

We develop methods for propagating and analyzing EPCI(Extended Process Capability Index) by using the error type that classifies into accuracy and precision. EPCI developed in this study can be applied to the three combined processes that consist of production, measurement and calibration. Little calibration work discusses while a great deal has been studied about SPC(Statistical Process Contol) and MSA(Measurement System Analysis). EPCI can be decomposed into three indexes such as PPCI(Production Process Capability Index), PPPI(Production Process Performance Index), MPCI(Measurement PCD, and CPCI(Calibration PCI). These indexs based on the type of error classification can be used with various statistical techniques and principles such as SPC control charts, ANOVA(Analysis of Variance), MSA Gage R&R, Additivity-of-Variance, and RSSM(Root Sum of Square Method). As the method proposed is simple, any engineer in charge of SPC. MSA and calibration can use efficientily in industries. Numerical examples are presentsed. We recommed that the indexes can be used in conjunction with evaluation criteria.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.5
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• pp.92-97
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• 2011

This paper deals with the improvement of electrode installation for measurement of ground resistance through investigation on the spot in buildings. The investigation was carried out for an earthing terminal board for measurement of ground resistance, installation of auxiliary electrode, etc. The criteria value is set up by measuring method of ground resistance in international standard. In case of inadequate installation of auxiliary electrode, a relative error is analyzed and adequate installation method of auxiliary electrode is proposed. As a consequence, it is necessary to write direction of ground and equipment, and separate auxiliary electrode for measurement of ground resistance in order to minimize measuring error.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.305-312
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• 2005

In the cluster analysis, Hotelling's $T^2$ can be used to estimate the unknown number of clusters based on the idea of multiple comparison procedure. Especially, its threshold is obtained according to the probability of committing the type one error. Examples are used to compare Hotelling's $T^2$ with other classical location test statistics such as Sum-of-Squared Error and Wilks' $\Lambda$ The hierarchical clustering is used to reveal the underlying structure of the data. Also related criteria are reviewed in view of both the between variance and the within variance.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4170-4180
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• 2022

The task complexity (TACOM) measure was previously developed to quantify the complexity of proceduralized tasks conducted by nuclear power plant operators. Following the development of the TACOM measure, its appropriateness has been validated by investigating the relationship between TACOM scores and three kinds of human performance data, namely response times, human error probabilities, and subjective workload scores. However, the information reflected in quantified TACOM scores is still insufficient to determine the levels of complexity of proceduralized tasks for human reliability analysis (HRA) applications. In this regard, the objective of this study is to suggest criteria for determining the levels of task complexity based on logistic regression between human error occurrences in digitalized main control rooms and TACOM scores. Analysis results confirmed that the likelihood of human error occurrence according to the TACOM score is secured. This result strongly implies that the TACOM measure can be used to identify the levels of task complexity, which could be applicable to various research domains including HRA.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.963-973
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• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.

• Journal of Korean Society of Rural Planning
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• v.10 no.3 s.24
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• pp.41-51
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• 2004

This study aims to develop a potential evaluation method for urban spatial expansion using remote sensing (RS) and geographic information system (GIS). A multi-criteria evaluation method with several criteria and their weighting values was introduced to evaluate the score and quantification of the potential surface around the existing cities. The six criteria with one geographic factor, slope, and five accessibility factors, time distance from center of the city, national road, interchange of expressway, a big city, and station, were defined for the potential. RS techniques were applied for classification of the actual urban expansion maps between two periods, and GIS functions were used for score of accessibility criteria with a distance decay function from geographic, road and several point maps, which was developed in this study. The new methodology was applied to a test area, Suwon, between 1986 and 1996. In order to optimize the six weighting values, this study made new findings to search the optimal combination of the weighting values from new methodology, weighted scenario method for intensity order (WSM), combined with intensity order and AHP method, including a trial and error method for sensitivity analysis to make the intensity order. The optimal combination of the weighting values by the new method generated the optimal potential surface, considering spatial trend of urban expansion in the test area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• Education of Primary School Mathematics
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• v.20 no.3
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• pp.193-204
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• 2017

The purpose of the study was to investigate and develop a practical approach to integrating student-driven mathematical problems posing in mathematics instruction. A problem posing activity was performed during regular mathematics instruction. A total of 540 mathematical problems generated by students were recorded and analysed using systemic procedures and criteria. Of the problems, 81% were mathematically solvable problem and 18% were classified as error type problems. The Mathematically solvable problem were analysed and categorized according to the complexity level; 13% were of a high-level, 30% mid-level and 57% low-level. The error-type problem were classified as such within three categories: non-mathematical problem, statement or mathematically unsolvable problem. The error-type problem category was distributed variously according to the leaning theme and accomplishment level. The study has important implications in that it used systemic procedures and criteria to analyse problem generated by students and provided the way for integrating mathematical instruction and problem posing activity.

• Earthquakes and Structures
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• v.8 no.6
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• pp.1325-1348
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• 2015

Real-time hybrid testing (RTHT) involves virtual splitting of the structure into two parts: physical substructure that contains the key region of interest which is tested in a laboratory and numerical substructure that contains the remaining part of the structure in the form of a numerical model. This paper numerically assesses four step-by-step integration methods (Central difference method (CDM), Operator splitting method (OSM), Rosenbrock based method (RBM) and CR-integration method (CR)) which are widely used in RTHT. The methods have been assessed in terms of stability and accuracy for various realistic damping ratios of the physical substructure. The stability is assessed in terms of the spectral radii of the amplification matrix while the accuracy in terms of numerical damping and period distortion. In order to evaluate the performance of the methods, five carefully chosen examples have been studied - undamped SDOF, damped SDOF, instantaneous softening, instantaneous hardening and hysteretic system. The performance of the methods is measured in terms of a non-dimensional error index for displacement and velocity. Based on the error indices, it is observed that OSM and RBM are robust and performs fairly well in all the cases. CDM performed well for undamped SDOF system. CR method can be used for the system showing softening behaviour. The error indices indicate that accuracy of OSM is more than other method in case of hysteretic system. The accuracy of the results obtained through time integration methods for different damping ratios of the physical substructure is addressed in the present study. In the presence of a number of integration methods, it is preferable to have criteria for the selection of the time integration scheme. As such criteria are not available presently, this paper attempts to fill this gap by numerically assessing the four commonly used step-by-step methods.

• Geomechanics and Engineering
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• v.33 no.1
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• pp.1-9
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• 2023

The unconfined compression strength (UCS) of soils is commonly used either before or during the construction of geo-structures. In the pre-design stage, UCS as a mechanical property is obtained through a laboratory test that requires cumbersome procedures and high costs from in-situ sampling and sample preparation. As an alternative way, the empirical model established from limited testing cases is used to economically estimate the UCS. However, many parameters affecting the 1D soil compression response hinder employing the traditional statistical analysis. In this study, gene expression programming (GEP) is adopted to develop a prediction model of UCS with common affecting soil properties. A total of 79 undisturbed soil samples are collected, of which 54 samples are utilized for the generation of a predictive model and 25 samples are used to validate the proposed model. Experimental studies are conducted to measure the unconfined compression strength and basic soil index properties. A performance assessment of the prediction model is carried out using statistical checks including the correlation coefficient (R), the root mean square error (RMSE), the mean absolute error (MAE), the relatively squared error (RSE), and external criteria checks. The prediction model has achieved excellent accuracy with values of R, RMSE, MAE, and RSE of 0.98, 10.01, 7.94, and 0.03, respectively for the training data and 0.92, 19.82, 14.56, and 0.15, respectively for the testing data. From the sensitivity analysis and parametric study, the liquid limit and fine content are found to be the most sensitive parameters whereas the sand content is the least critical parameter.